The shocklet transform: a decomposition method for the identification of local, mechanism-driven dynamics in sociotechnical time series

Abstract We introduce a qualitative, shape-based, timescale-independent time-domain transform used to extract local dynamics from sociotechnical time series—termed the Discrete Shocklet Transform (DST)—and an associated similarity search routine, the Shocklet Transform And Ranking (STAR) algorithm,...

Full description

Bibliographic Details

Published in:	EPJ Data Science
Main Authors:	David Rushing Dewhurst, Thayer Alshaabi, Dilan Kiley, Michael V. Arnold, Joshua R. Minot, Christopher M. Danforth, Peter Sheridan Dodds
Format:	Article
Language:	English
Published:	SpringerOpen 2020-02-01
Subjects:	Nonparametric statistics Sociotechnical time series Time-domain filtering Social media
Online Access:	https://doi.org/10.1140/epjds/s13688-020-0220-x